The aim of behavior analysis has always been to apply technologies rooted in basic behavioral principles to problems of societal importance (e.g., Skinner, 1948; 1953; 1987). One such problem is the Tragedy of the Commons - a phenomenon arising from systemic failures among a community, leading to the total collapse of a critical resource (Hardin, 1968). Elinor Ostrom's Eight Design Principles were developed to provide a framework for the self-management of common pool resources (CPRs; Ostrom, 1990/2015). When applied as an independently manipulated variable, Ostrom's design principles have shown strong effects in the management of CPRs within the context of a tabletop board game Catan® (Smith & Becker, 2023). This preparation included both rewards (i.e., positive reinforcement) and sanctions (i.e., positive punishment) as a feature of the independent variable. However, it has been well documented that punishing and coercive contingencies can lead to problematic outcomes for individuals and societies (e.g., Sidman, 2001; Skinner, 1976). This study evaluated the effects of utilizing only rewarding consequences in lieu of sanctions in an effort to produce the previously observed control over self-management of a CPR, utilizing the previously adapted rules of the Catan® board game.

För organisationers långsiktiga framgångar är det avgörande att inte enbart rekrytera kompetenta medarbetare, utan också att behålla dem över tid. Belöningar har en stark roll i detta sammanhang, då de inte endast motiverar anställda, utan även fungerar som en drivkraft för att de ska ha en avsikt att stanna kvar. Studien syftar till att utveckla kunskap om vilken effekt monetära belöningar, icke-monetära belöningar och belöningsmatchning har på anställdas avsikt att stanna kvar på sin arbetsplats. Studien tillämpade en kvantitativ forskningsdesign och samlade in data från en internetbaserad enkätundersökning med ett bekvämlighetsurval av respondenter från olika branscher och åldersgrupper. Resultatet visade att när anställda blir belönade med frihet och ansvar som matchar deras önskemål ökar deras avsikt att stanna kvar på sin arbetsplats avsevärt. För att maximera effekten av belöningar som ökar anställdas avsikt att stanna kvar är det således viktigt för arbetsgivare att ta hänsyn till anställdas behov av att ha frihet och tilldelas ansvar på arbetsplatsen. Trots att vi inte med säkerhet kan säga att monetära och icke-monetära belöningar i sin helhet påverkar anställdas avsikt att stanna kvar, finns en tydlig koppling mellan anställdas nöjdhet med sin nuvarande lön och deras avsikt att stanna kvar. Vi har kunnat påvisa att nöjdhet med lön är en avgörande faktor för att få anställda att stanna kvar på sin arbetsplats. Studien har bidragit till den viktiga insikten att det är fördelaktigt för organisationer att i första hand erbjuda löner som anställda är nöjda med och som matchar anställdas förväntningar för att behålla dem på arbetsplatsen. / For organizations’ long-term success, it is crucial not only to recruit competent employees but also to retain them over time. Rewards play a significant role in this context, as they not only motivate employees, but also serve as a driver for them to have an intention to stay. This study aims to investigate how monetary rewards, non-monetary rewards and reward matching influence employees’ intention to stay. The study applied a quantitative research design and collected data from an internet-based survey with a convenience sample of respondents from various industries and age-groups. The results showed that when employees are rewarded with freedom and responsibility that match their desires, their intention to stay at their workplace increases significantly. To maximize the effect of rewards on increasing employees’ intention to stay, it is therefore important for employers to consider employees’ needs or freedom and responsibility in the workplace. Although we cannot say with certainty that monetary and non-monetary rewards as a whole affect employees’ intention to stay, there is a clear link between employees’ satisfaction with their current salary and their intention to stay. We have been able to demonstrate that satisfaction with salary is a crucial factor in getting employees to stay at their workplace. The study has contributed to the important insight that it is advantageous for organizations to primarily offer salaries that employees are satisfied with and match their expectations, in order to retain them.

The purpose of the present investigation was to assess the relationships among the contingency of teachers' reactions as perceived by the pupils, the pupils' academic performance, and internality. One might expect that children who perceive their teacher as contingently rewarding and punishing would achieve higher grades and test scores than those who view their teachers' reactions as unrelated to their behavior. It is believed that children's perceptions of the contingencies of their teacher's responses may be more highly related to achievement behavior than the teacher's actual distribution of rewards and punishments. Perceived contingency of punishments and rewards may be important determiners of achievement. The perception of punishments as noncontingent is likely to be negatively related to achievement; however, the same may not be true of noncontingent reward. Indiscriminate dispersion of rewards could have a motivating effect or, as one might infer from Paris & Cairns (1972), no effect at all. Internality and achievement are expected to be positively related, perhaps more so for boys than for girls, as the trend of previous evidence suggests. Because of conflicting reports, no firm expectation can be formulated with regard to sex differences and the effectiveness of IAR+ versus IAR- scores.

This new economic era is characterized by organizations managing a diverse workforce across different generations. These generations have different work values, goals, and expectations on their employer, which poses various challenges for human resource managers in managing and retaining employees from different generations. The most recent generation that is currently entering the workforce is generation Y, and they are described as the younger generation with high employee turnover and reluctance to pledge long-term work commitments. Therefore, it is in the interest of organizations to tailor reward schemes that resonate with generation Yers in fostering organizational commitment. Thus, this thesis aims to examine how extrinsic and intrinsic rewards affect organizational commitment in generation Y. To answer these questions, this thesis reviews previous literature and use the self-determination theory to see how the different rewards affect the organizational commitment of generation Y. This study has been conducted through interviews with employees that are born within the age spectrum of generation Y (1980-1999) to understand how reward systems affect organizational commitment in generation Y employees. This thesis found that intrinsic rewards affect organizational commitment in a far more positive manner than extrinsic rewards. Furthermore, intrinsic rewards resonate to a greater extent with the employees from generation Y and should, therefore, be a priority for organizations. Moreover, this thesis concludes that intrinsic rewards can more easily satisfy the basic psychological needs, which are, as according to the self-determination theory, crucial to foster organizational commitment.

Thesis (M. Ed.)--University of Hong Kong, 1995. / Includes bibliographical references (leaf 120-123).

Thesis (M. Ed.)--University of Hong Kong, 1991. / Includes bibliographical references (leaf 86-91).

Thesis (M.Ed.)--University of Hong Kong, 1991. / Includes bibliographical references (leaf 86-91). Also available in print.

Thesis (M.Ed.)--University of Hong Kong, 1995. / Includes bibliographical references (leaves 120-123). Also available in print.

Esta dissertação de mestrado apresenta um estudo sobre os efeitos de diferentes funções de recompensa, aplicadas em aprendizado por reforço multiagente, para o problema de roteamento de veículos, em redes de tráfego. São abordadas duas funções de recompensas que diferem no alinhamento do sinal numérico enviado do ambiente ao agente. A primeira função, chamada função individual, é alinhada à utilidade individual do agente (veículo ou motorista) e busca minimizar seu tempo de viagem. Já a segunda função, por sua vez, é a chamada difference rewards, essa é alinhada à utilidade global do sistema e tem por objetivo minimizar o tempo médio de viagem na rede (tempo médio de viagem de todos os motoristas). Ambas as abordagens são aplicadas em dois cenários de roteamento de veículos que diferem em: quantidade de motoristas aprendendo, topologia e, consequentemente, nível de complexidade. As abordagens são comparadas com três técnicas de alocação de tráfego presentes na literatura. Resultados apontam que os métodos baseados em aprendizado por reforço apresentam desempenho superior aos métodos de alocação de rotas. Além disso, o alinhamento da função de recompensa à utilidade global proporciona uma melhora significativa nos resultados quando comparados com a função individual. Porém, para o cenário com maior quantidade de agentes aprendendo simultaneamente, ambas as abordagens apresentam soluções equivalentes. / This dissertation presents a study on the effects of different reward functions applyed to multiagent reinforcement learning, for the vehicles routing problem, in traffic networks. Two reward functions that differ in the alignment of the numerical signal sent from the environment to the agent are addressed. The first function, called individual function is aligned with the agent’s (vehicle or driver) utility and seeks to minimize their travel time. The second function, is called difference rewards and is aligned to the system’s utility and aims to minimize the average travel time on the network (average travel time of all drivers). Both approaches are applied to two routing vehicles’ problems, which differ in the number of learning drivers, network topology and therefore, level of complexity. These approaches are compared with three traffic assignment techniques from the literature. Results show that reinforcement learning-based methods yield superior results than traffic assignment methods. Furthermore, the reward function alignment to the global utility, provides a significant improvement in results when compared with the individual function. However, for scenarios with many agents learning simultaneously, both approaches yield equivalent solutions.

Esta dissertação de mestrado apresenta um estudo sobre os efeitos de diferentes funções de recompensa, aplicadas em aprendizado por reforço multiagente, para o problema de roteamento de veículos, em redes de tráfego. São abordadas duas funções de recompensas que diferem no alinhamento do sinal numérico enviado do ambiente ao agente. A primeira função, chamada função individual, é alinhada à utilidade individual do agente (veículo ou motorista) e busca minimizar seu tempo de viagem. Já a segunda função, por sua vez, é a chamada difference rewards, essa é alinhada à utilidade global do sistema e tem por objetivo minimizar o tempo médio de viagem na rede (tempo médio de viagem de todos os motoristas). Ambas as abordagens são aplicadas em dois cenários de roteamento de veículos que diferem em: quantidade de motoristas aprendendo, topologia e, consequentemente, nível de complexidade. As abordagens são comparadas com três técnicas de alocação de tráfego presentes na literatura. Resultados apontam que os métodos baseados em aprendizado por reforço apresentam desempenho superior aos métodos de alocação de rotas. Além disso, o alinhamento da função de recompensa à utilidade global proporciona uma melhora significativa nos resultados quando comparados com a função individual. Porém, para o cenário com maior quantidade de agentes aprendendo simultaneamente, ambas as abordagens apresentam soluções equivalentes. / This dissertation presents a study on the effects of different reward functions applyed to multiagent reinforcement learning, for the vehicles routing problem, in traffic networks. Two reward functions that differ in the alignment of the numerical signal sent from the environment to the agent are addressed. The first function, called individual function is aligned with the agent’s (vehicle or driver) utility and seeks to minimize their travel time. The second function, is called difference rewards and is aligned to the system’s utility and aims to minimize the average travel time on the network (average travel time of all drivers). Both approaches are applied to two routing vehicles’ problems, which differ in the number of learning drivers, network topology and therefore, level of complexity. These approaches are compared with three traffic assignment techniques from the literature. Results show that reinforcement learning-based methods yield superior results than traffic assignment methods. Furthermore, the reward function alignment to the global utility, provides a significant improvement in results when compared with the individual function. However, for scenarios with many agents learning simultaneously, both approaches yield equivalent solutions.